Forward Deployed Engineer – Data-as-a-Service

🕒 April 1

🏢🏡 New York City – Hybrid

💵 $172k - $300k / year

⏰ Full Time

🟡 Mid-level

🟠 Senior

👷🏻‍♀️ Engineer

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Snorkel AI

WebsiteLinkedInAll Job Openings

51 - 200 employees

Founded 2019

🤖 Artificial Intelligence

💸 Finance

⚕️ Healthcare Insurance

Artificial Intelligence • Finance • Healthcare Insurance

Snorkel AI is an innovative platform that specializes in providing expert-level training and evaluation data tailored for machine learning models. Their service, known as Expert Data-as-a-Service, enables organizations to create high-quality datasets for AI applications, significantly accelerating model delivery and enhancing accuracy. Founded from research at Stanford, Snorkel partners with leading AI companies to push the boundaries of AI capabilities across various sectors, including finance and healthcare.

📋 Description

• Build and deploy evaluators, design and implement quality measurement systems to validate project outputs and ensure deliverables meet client expectations • Generate synthetic datasets by developing or adapting existing pipelines to accelerate client engagements and augment training data • Package and deliver production-grade datasets with standardized formatting, comprehensive documentation, and quality assurance • Configure and build custom applications and off-platform solutions for non-standard or specialized client requirements • Define production specifications and workflows, securing technical alignment with client teams to enable seamless go-live transitions • Provide ongoing technical support to Delivery Managers, addressing complex questions, resolving technical blockers, and supporting customer rebuttals • Maintain specification consistency and alignment across customer and internal teams throughout the engagement lifecycle • Identify and document workflow best practices and automation opportunities, collaborating with DaaS Engineering to continuously improve delivery capabilities • Maintain solution leaderboards and execute custom model benchmarking on existing datasets to demonstrate technical capabilities • Drive continuous improvement of technical assets, evaluation frameworks, and delivery processes to enhance speed, quality, and scalability

🎯 Requirements

• 4+ years of experience in data science, engineering, or solution development roles. Strong practical experience with Python and SQL data tooling required • Familiarity with ML and LLM-based solutions, applying ML techniques in production contexts, and validation and evaluation of ML and LLM-based • Experience integrating systems via API

🏖️ Benefits

• Equity in the form of employee stock options